Collection of Meta Information with User-Generated Question Answer Pairs and its Reflection for Improving Expressibility in Response Generation

• Kodama Takashi

  Kyoto University, Graduate School of Informatics; this is the work done during the internship at NTT.

• Higashinaka Ryuichiro

  NTT Corporation; Nagoya University, Graduate School of Informatics

• Mitsuda Koh

  NTT Corporation

• Masumura Ryo

  NTT Corporation

• Aono Yushi

  NTT Corporation

• Nakamura Ryuta

  DWANGO Co., Ltd.

• Adachi Noritake

  DWANGO Co., Ltd.

• Kawabata Hidetoshi

  DWANGO Co., Ltd.

抄録

This paper concerns the problem of realizing consistent personalities in neural conversational modeling by using user generated question-answer pairs as training data. Using the framework of role play-based question-answering, we collected single-turn question-answer pairs for particular characters from online users. Meta information was also collected such as emotion and intimacy related to question-answer pairs. We verified the quality of the collected data and, by subjective evaluation, we also verified their usefulness in training neural conversational models for generating responses reflecting the meta information, especially emotion.

収録刊行物

• 自然言語処理

  自然言語処理 28 (1), 136-159, 2021

  一般社団法人　言語処理学会

キーワード

• Data Collection
• Meta Information
• User-generated Content
• Utterance Generation
• Question-Answering

詳細情報

• CRID: 1390568838438509952
• NII論文ID: 130007998391
• DOI: 10.5715/jnlp.28.136
• ISSN: 21858314
• ISSN: 13407619
• Web Site: https://www.jstage.jst.go.jp/article/jnlp/28/1/28_136/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可